devops

A client's deployment kept failing in staging but not locally. The root cause wasn't code — it was sixty-seven environment variables spread across five files with no documentation and no single source of truth.

We practiced deployments religiously but never tested a rollback. When a release broke checkout and we hit the big red button, we found out half the system couldn't actually go backward.

Every deploy was losing a handful of HTTP requests, but nobody noticed until a payment callback disappeared. The fix wasn't in the deployment pipeline — it was in the application code that never learned how to shut down.

A client's pods were getting OOMKilled during peak traffic, but the team spent days chasing application bugs. The real problem was resource limits that nobody had revisited since the initial cluster setup.

A client had six monitoring tools and still couldn't diagnose a production incident in under an hour. The problem wasn't the tools — it was what happens when observability grows by accretion instead of design.

A client's staging environment had drifted so far from production that developers stopped using it. Tests passed in staging and failed in prod. Tests failed in staging and passed in prod. Eventually the team just stopped looking.

A consulting engagement where we finally opened the cloud bill and found forgotten dev environments, runaway log storage, and a data pipeline reprocessing everything from scratch every night.

A 47-minute build pipeline had become sacred infrastructure. When we finally opened it up, we found cargo-culted steps, redundant checks, and a team afraid of their own tooling.

We built a canary deployment pipeline with automated rollbacks. It still let a bad release through to 100% of users. Here's what went wrong.